Vol.2, No.12, 1382-1389 (2010) Health
doi:10.4236/health.2010.212205
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
Impact of nutritional support on nutritional status and
nitrogen balance in surgical patients of a developing
country
Ravindra Singh Mohil1*, Nitisha Narayan1, Namrata Singh2, Asheesh Praveen Lal1,
Vishnubhatla Sreenivas3, Dinesh Bhatnagar1
1Department of Surgery, V.M. Medical College and Safdarjang Hospital, New Delhi, India;
*Corresponding Author:
[e-mail], ,
2Department of Gastroenterology and Human Nutrition, AIIMS, New Delhi, India;
3 Department of Biostatistics, AIIMS, New Delhi, India.
Received 4 September 2010; revised 8 October 2010; accepted 19 October 2010
ABSTRACT
To assess the nutritional status, its change after
surgery and impact of nutritional support on uri-
nary nitrogen losses (UNL) and nitrogen balance
(NB) based on changing serum albumin levels
in a developing country, 89 patient (58 M) aged
39 yrs ±15 were studied. Nutritional assessment
was done at admission and 2 w eeks postopera-
tively. UNL and NB was assessed on postopera-
tive day one (D1), two (D2), four (D4), six (D6),
eight (D8) and eleven (D11) respectively. Malnu-
trition varied from 27 (30.3%) using body mass
index to 78 (87%) by triceps skin fold thickness.
Patients with falling or static serum albumin le-
vels (Group I) showed a significant decrease (‘p’
= 0.001) in their nutritional param et ers co mpar ed
to those with increasing albumin (Group II).
Postoperatively till D2 both groups had similar
negative NB but Group II improved earlier to
become positively balanced by D11 (‘p’ < 0.001).
Regression analysis of nitrogen intake (Ni) on
UNL on each day revealed negative association
till D2 to become positively associated from D4
onwards being significant on D4 (‘p’ = 0.001) &
D6 (‘p’ = 0.05*). There is a significant nutritional
depletion after surgery especially in patients w ith
falling/static serum albumin levels and NB im-
proves earlier in patients with rising albumin
levels. Increasing Ni helps in decreasing UNL.
Keywords: Nutritional Status; Nitrogen Balance;
Serum Albumin
1. INTRODUCTION
In spite of India’s rapid economic growth, adult mal-
nutrition is still widely prevalent in the community. De-
fining malnutrition may be a challenge unless we realise
what we actually mean by malnutrition. Prevalence of
malnutrition depends upon the criteria used and nutri-
tional status has been defined by multiple ways [1,2].
Different measures, different equipment and different
formulae are being used, leading to different outcome
both at individual and population level. Therefore ap-
plying western standards for nutritional assessment in
developing countries may give misleading results.
Hospital under-nutrition, although recognised as of
clinical significance, still remains widely undiagnosed/
underestimated even in the west where around 25% to
35% can be malnourished [3-5]. Besides nutritional defi-
ciency, presence of inflammatory activity leads to loss of
body cell mass (BCM) by inducing catabolism and both
these factors combined lead to malnutrition [6]. In de-
veloping countries where under-nutrition is endemic and
chronic infection is widely prevalent, malnutrition is
more likely as both these factors operate simultaneously,
strengthening each other and mutually aggravating their
severity [7]. In first 3-5 days following surgery pro-inflam-
matory state is reversed by the ant-inflammatory healing
response the adequacy of which can be judged based on
negative fluid balance, increasing albumin, loss of edema,
clinical improvement, increasing haemoglobin etc. There-
fore, changing serum albumin levels is now being used
more as an inflammatory marker than nutritional pa-
rameter [7]. Urinary nitrogen losses (UNL) and nitrogen
balance (NB) reflect the intensity of this inflammatory
response and has been widely used to monitor the ade-
quacy of nutritional support postoperatively [8,9].

R. S. Mohil et al. / Health 2 (2010) 1382-1389
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The present study was therefore undertaken to assess
the nutritional status and its change in patients under-
going various types of surgeries in a developing country
where malnutrition is endemic and nutritional standards
are still not defined. The role of serum albumin as a
marker of nutritional and inflammatory activity (increasing
or decreasing/static) was studied. UNL and NB were
studied to see loss patterns and when the pro-inflammatory
state is being reversed in our group of patients. Based on
changing albumin levels (inflammatory activity), NB
pattern following surgery was also examined along with
the impact of nitrogen intake (nutritional support) on
UNL.
2. MATERIALS AND METHODS
Participants: The study was conducted in the surgical
ward of a tertiary care, free, government hospital in the
capital city of a developing country over a period of 18
months. The study was conducted according to the guide-
lines laid down in the Declaration of Helsinki and was
approved by the hospital ethics committee. Witnessed
verbal informed consent was obtained from all patients
and formally recorded in the case sheet. Patients < 12
years of age, those with enterocutaneous fistula, uncons-
cious or clinically unstable, not taken up for surgery or
died were excluded from the study.
Nutritional assessment: On admission a detailed clini-
cal examination related to the main disease along with
nutritional assessment was carried out. The nutritional
assessment was performed within 48 hours of admission;
using different nutritional indices.This included a detailed
anthropometry, biochemical and immunological assess-
ment. The assessment was repeated at two weeks post-
operatively. Anthropometry using standard techniques
included height, weight, body mass index (BMI), mid
arm circumference (MAC) and triceps skin fold thick-
ness (TSF). Mid arm muscle circumference (MAMC)
was derived from the equation MAMC = MAC- π × TSF.
Biochemical assessment included haemoglobin, serum
albumin (S. Albumin), creatinine height index (CHI). From
the estimated 24 hours urinary creatinine excretion, cre-
atinine height index (CHI) was calculated using the origi-
nal standards of Bristrian (1976) [10]. Immunological
parameters included total lymphocyte count (TLC) de-
rived by multiplying total leucocyte count with percent
lymphocyte count and delayed cutaneous hypersensitiv-
ity (DH). Purified protein derivative (PPD) one TU/0.1 ml
was injected intradermally on the ventral aspect of fo-
rearm to measure delayed hypersensitivity response 48
hours.
Urinary Nitrogen loss & Nitrogen balance: To cal-
culate nitrogen intake protein content of various foods
was seen from the tables of food composition of India
[11]. Twenty four hours urinary nitrogen loss was meas-
ured using the micro-Kjeldahl technique of total nitrogen
assessment in the sample [12]. Nitrogen balance (NB)
was calculated using the formula: NB = Nitrogen intake
– Urinary Nitrogen loss + 1 g × number of stools. [12]
Urinary Nitrogen loss (UNL) and NB was measured
on postoperative day 1 (D1), 2 (D2), 4 (D4), 6 (D6), 8
(D8) and 11(D11). Protein intake was calculated by 24
hours recall method. The nitrogen intake was calculated
using the formula:
N2 intake/day = protein intake (gms/day)/6.25
Nutritional categorisation: The anthropometric val-
ues were compared with percentages of normal values for
age and sex. TSF values < 12.5 mm for males and < 16.5
mm for females were taken as malnourished. The stan-
dard values for MAMC were 25.3 cm for males and 23.2
cm for females. Values were categorized as severe if <
60% of standard, moderate 61-80% of standard and mild
when 81-90% of standard. Values > 90% of standard were
considered normal [13]. Body mass index which is de-
rived by dividing body weight with height in meter square
is a good indicator for nutritional assessment. It is increa-
singly being used for assessing and grading of nutritional
status. Values < 18.5 were categorized as malnourished,
18.5 to 25 were taken as normal and those with > 25 were
labeled as overweight.
Haemoglobin values in adult males of < 12 gm % and
< 11.5 gm % in females were considered anaemic based
on standard values [14]. Total lymphocyte count > 2000/
mm3 was considered normal, between 1200-1999/mm3
as mild depletion, 800-1199 as moderate depletion and
those < 800 as severely depleted [15]. Serum albumin >
3.5 gm % were considered normal. Concentrations be-
tween 2.8-3.5 gm %, between 2.1-2.7 gm % and < 2.1
gm % were categorized as mild, moderate and severe dep-
letion respectively. [15] Standards laid down by Bristrian
were followed to calculate creatinine height index (CHI)
[10]. The response to intradermal injection of PPD anti-
gen was evaluated at 48hrs after the test dose. Any indu-
ration > 5 mm and an erythema of more than 15-20 mm
was considered positive [16]. Response other than this
was considered negative.
Statistical Analysis: Data was entered into Microsoft
Excel and Stata version 9.2 statistical software was used
for data analysis. Descriptive statistics such as mean, stan-
dard deviation etc. for continuous covariates and per-
centage and proportions for categorical variables were
reported. Independent t-test has been carried out for the
comparison of continuous variables between two groups.
The changes in various nutritional parameters before oper-
ation and after operation in the two groups, i.e. albumin
decreasing/not changing and albumin increasing were
compared using paired t-test. The direct association be-

R. S. Mohil et al. / Health 2 (2010) 1382-1389
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1384
tween nitrogen balance (NB) and nitrogen intake (NI)
cannot be studied because NB calculation involves NI.
Therefore, the association between NI & UNL was stu-
died at different time points after surgery to see the dy-
namics of effect of NI on UNL. Simple linear regression
analysis of UNL was carried out on Ni at each day for
this purpose. Categorical variables were compared by Chi-
square test or Fisher’s exact test wherever applicable.
Generalised Estimating Equation (GEE) has been ap-
plied to see the overall changes in UNL and NB over the
time (D1 to D11). The level of significance was set at ‘p’
value < 0.05.
3. RESULTS
Sixteen patients out of 105 evaluated were excluded
because of various reasons. Four patients had enterocu-
taneous fistula following surgery done outside, 5 patients
were in ICU postoperatively for more than 5-7 days, five
patients died and two patients left against medical advice
before the study period was over. Out of the total 89
patients finally included in the study, 58 were males and
34 females. The mean age was 39.19 yrs + 14.63 (range
17-80 year). For analysis patients were divided into two
groups based on changing serum albumin levels into
those with decreasing/static (Group I) or increasing (Group
II) values.
Initial nutritional assessment: The prevalence of mal-
nourished patients varied when different parameters
were used for nutritional assessment. When BMI was
used 27 (30.3%) patients were found to be malnourished.
This increased to a maximum of 78 (87%) by TSF. The
degree of malnutrition varied between these two extremes
using other nutritional parameters as shown in Table1.
Biochemical parameters like serum albumin and total
lymphocyte count were lower than normal in 20 (22.47%)
and 48 (53.93%) of the patients respectively on initial
assessment. Only five (5.6%) patients showed energy to
PPD. Patients with BMI < 18.5 had significantly lower
nutritional parameters (Table 2).
Change in nutritional status: Postoperatively there was a
significant decrease in various nutritional parameters of
the whole group except serum albumin. Albumin de-
creased or remained same (Group I) in 66 (74.15%) &
improved (Group II) in the remaining 23 (25.85%) pa-
tients. At the end of two weeks, Group I patients had a
significant decrease in their weight and all the other nu-
tritional parameters. Compared to this, Group II patients
showed improvement in all their other nutritional para-
meters although this was significant for weight, tsf and
haemoglobin only (Table 3).
UNL & NB: UNL were highest on day six (D 6) and
returned to preoperative levels by approximately D11 for
the whole group. UNL were depended on the extent and
Table 1 .Classification of subjects into various grades of nutritional status using different nutritional parameters.
Nutritional
parameter
Nutritional status
Severe
< 60%
Moderate
61-80%
Mild
81-90%
Normal
> 90%
S. Albumin 0 6 (6.7) 14 (15.73) 69 (77.52)
TLC 1 (1.1) 15 (16.85) 32 (35.95) 41 (46.06)
TSF 49 (55.05) 18 (20.22) 11 (12.35) 11 (12.35)
MAMC 0 15 (16.85) 26 (29.21) 48 (53.93)
CHI 4 (4.44) 37 (41.57) 20 (22.47) 28 (31.46)
Values are given as numbers and percentages in parentheses
Table 2. Comparison of nutritional parameters based on BMI.
Nutritional
parameter
BMI < 18.5 (n = 27) BMI > 18.5(n = 62)
‘p’ value
Normal Undernourished Normal Undernourished
TSF 0 27 (100%) 11(17.70%) 51(82.3%) 0.03*
MAMC 7 (25.9%) 20 (74.1%) 42 ((67.7%) 20 (32.3%) < 0.001*
Haemoglobin 1(3.7%) 26 (96.27%) 31(50%) 31(50%) < 0.001*
DH 22 (81.5%) 5 (18.5%) 62 (100%) 0 0.01*
S. Albumin 13 (48.1%) 14 (51.85%) 56 (90.3%) 6 (9.67%) < 0.001*
*Significant

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Table 3. Comparison and change in nutritional parameters after surgery as compared to before surgery in patients with albumin fall-
ing/ no change (Group I) vs. those with rising albumin levels (Group II).
Nutritional
parameter
Albumin- no change /falling Group I
(n = 66)
Albumin rising Group II
(n = 23)
Pre-op Post -op
Change
Post- Pre
(95% CI*)
‘p’ valuePre-op Post-op
Change
Post- Pre
(95% CI*)
‘p’ value
Weight 57.33
± 8.50
56.16
± 8.49
1.17
(0.82 1.51) 0.001* 48.10 ± 8.87
48.84
± 8.39
–0.74
(-1.49 0.01) 0.001*
MUAC 25.80
±2.91
25.00
± 3.28
0.80
(0.59 1.01) 0.001* 22.15 ± 2.53
22.46
± 2.62
–0.31
(–0.83 0.21) 0.001*
TSF 0.82
± 0.38
0.73
± 0.38
0.09
(0.06 0.11) 0.001* 0.71 ± 0.46
0.78
± 0.45
–0.06
(–0.11 –0.02) 0.01*
MAMC 23.29
± 2.44
22.78
± 2.74
0.50
(0.23 0.79) 0.001* 19.89 ± 1.94
20.13
± 2.03
–0.24
(–0.84 0.36) 0.42
CHI 86.25
± 25.04
76.06
± 13.57
10.19
(5.66 14.73) 0.001* 77.56 ± 22.23
77.77
± 15.16
–0.21
(–6.49 6.07) 0.94
Hb 11.44
± 1.52
10.75
± 1.63
0.69
(0.47 0.90) 0.001* 9.91 ± 1.7510.92 ±1.30
–1.01
(–1.39 –0.63) 0.001*
TLC 2124
± 602
2029
± 619
95
(50 140) 0.001* 1629 ± 659
1669
± 603
–40
(–118 –38) 0.30
CI – Confidence interval; *Significant
type of surgery. It was < 10 g/24 hours in thyroidectomy,
appendectomy, hernia surgery and exploratory laprotomy.
Moderate amount of nitrogen loss were seen in mas-
tectomy (15 g/ 24 hours), pyelolithotomy (13 g/ 24
hours), gastrectomy, abdomino-perineal resection (19 g/ 24
hours), and Commando’s operation (with radical neck
dissection) (25 g/ 24 hours). It was very high after tho-
racotomy (45 g/ 24 hours) and Mc Keown esophagect-
omy (70 g/ 24 hours) done in two patients each respec-
tively.
Nitrogen intake (NI) also influenced the mean UNL,
from having no association on D1 to being negatively
associated on D2, it improved D4 onwards to become
positively associated till D11. As the nitrogen intake (NI)
improved, UNL also improved, though this reached sta-
tistical significance on D4 & D6 only (Table 4).
Similar to UNL, NB also became increasingly nega-
tive to reach a peak on D6, returning to starting D1 le-
vels by D11. Compared to patients with falling or static
S. Albumin (Group I), the NB started improving earlier
in patients with rising S. Albumin (Group II). Initially
till D2 there was no significant difference in the mean
negative NB between the two groups, but D3 onwards
Gr. II patients had lesser negative NB becoming positive
by D11. This was borderline significant (‘p’ = 0.06) on
D4 and became increasingly significant thereafter till
D11 (Table 5).
4. DISCUSSION
An ideal tool for nutritional assessment should be
sensitive, accurate, reproducible by various observers,
relevant in health and illness, applicable to all patients at
the bedside, and cost-effective. The diagnosis of malnu-
trition is generally based on objective methods of nutri-
tional assessment including assessment of dietary intake,
weight loss, anthropometric data, determination of cell
mediated immunity, biochemical parameters, body func-
tion and composition analysis [17,18]. Despite a large
body of work on nutritional risk screening and assess-
ment there is no complete agreement on the optimal
method for either nutritional screening or assessment.
This is due to lack of consensus regarding definitions
and assessment of nutritional status.
Malnutrition has been defined in different ways.
ESPEN consensus report defined it as “a state resulting
from lack of intake of nutrition leading to altered body
composition (decreased fat free mass (FFM) but specifi-
cally body cell mass (BCM)) and diminished function”.
[19] However, Norman et al [6] highlighted the role of
inflammatory activity as a contributory factor to malnu-
trition leading to inclusion of metabolism as factor in
defining malnutrition. Further, over-nutrition has not been
included in the above definition. Based on these facts
Soeters et al [7] have proposed that malnutrition may be
defined as “a subacute or chronic state of nutrition in
which a combination varying degrees of over- or under-
nutrition and inflammatory activity have led to a change
in body composition and diminished function”.
In a developing country like ours defining malnutri-
tion may be a challenge as there is limited data on vari-

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1386
ous nutritional parameters and the data collected in the
Table 4. Association between Nitrogen intake (Ni) & Urinary Nitrogen Losses (UNL) day wise (n=89).
Day of assessment Ni
Mean ± SD
UNL
Mean ± SD
Regression
Coefficient# 95% CI ‘p’ value
D 1 2.09 ± 1.99 7.26 ± 0.37 –0.30 (–0.66 0.07) 0.11
D 2 0.27 ± 0.85 10.79 ± 0.77 –2.36 (–4.18 0.61) 0.01*
D 4 4.10 ± 7.72 15.74 ± 1.29 0.74 (0.44 1.04) 0.001*
D 6 5.02 ± 7.98 17.18 ± 1.51 0.38 (0.003 0.75) 0.05*
D 8 5.98 ± 8.74 15.98 ± 1.50 0.15 (–0.20 0.49) 0.40
D 11 6.76 ± 9.38 12.26 ± 1.03 0.06 (–0.15 0.29) 0.55
#Regression coefficient of Ni on UNL; *Significant
Table 5. Change in Nitrogen Balance (NB) in the two groups based on changing albumin levels.
Day of assessment
Nitrogen Balance
Difference (95% CI) ‘p’ value
Albumin ↓ or
no change
(Group I)
Alb. ↑
(Group II)
D 1 –6.36 ± 4.48 –6.05 ± 3.83 –0.31
(–2.39 1.77) 0.77
D 2 –11.65 ± 7.74 –11.54 ± 7.32 –0.11
(–3.79 3.56) 0.95
D 4 –14.03 ± 10.83 –9.07 ± 10.58 –4.96
(–10.14 0.22) 0.06
D 6 –15.04 ± 14.05 –8.17 ± 15.99 –6.87
(–13.65 0.11) 0.05*
D 8 –14.30 ± 16.33 –1.95 ± 10.37 –12.34
(–19.59 -5.10) 0.001*
D 11 –10.13 ± 12.28 3.54 ± 9.43 –13.67
(–19.27 -8.08) <0.001*
*Significant
community is anthropometric. The problem is further
compounded by the presence of chronic energy defi-
ciency syndrome (CED). [20] This has been defined as a
“steady state” where an individual is in energy balance,
i.e. the energy intake equals the energy expenditure, de-
spite the low body weight and low body energy stores.
In the present study we faced a problem of defining
malnutrition using any single tool. Using various nutri-
tional parameters individually, prevalence of malnutri-
tion varied between 22% (serum albumin) to 87% using
TSF. Majority of the patients had very low fat (55% se-
vere depletion) and muscle mass (46% moderate to mild
depletion). As Indian standards are not available for fat
and muscles mass, applying western values gave a very
high prevalence of malnutrition in our study. This high-
lights the importance of having standards and cut-off
points for Asian population which should be related
more to functional parameters such as immune function,
muscle function, clinical outcome or quality of life. Pham
NV et al highlighted this in their study where they showed
that large proportion of patients rated as moderate to
severely malnourished based on subjective global as-
sessment (SGA) had normal muscle mass and strength
[21].
BMI is the most widely used anthropometric index for
the assessment of nutritional status in adults as it reflects
the effect of both acute and chronic energy deficiency/
excess. The use of BMI as a measure of nutritional as-
sessment is limited by its poor sensitivity with respect to
baseline assessment, particularly for chronically under-
nourished as well overweight patients. For example those
who are stunted and have low body weight may have
normal BMI. Similarly, individuals in the high-
normal range can undergo significant change in their
nutritional status prior to estimation of having an abnormal
status or being nutritionally depleted [18].
We observed 27 (30%) of our patients had a BMI of
less than 18.5. This high incidence is in contrast to the
west where almost 30% of the population is overweight
(BMI 25 to 29.9 Kg/M2) and another 30% is obese
(BMI > 30 Kg/M2) with only 5-7% patients having a
BMI < 18.5 [18]. Naidu and Rao observed that in certain
areas of rural India up to 50% of the population with low
incomes and land holdings suffer from chronic energy
deficiency (CED) and have low BMI (< 18.5 Kg/m2 )
[20]. Most of these are physiologically well adapted till

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the disease process starts.
In the present study, patients with a BMI of < 18.5 had
significantly greater derangement in their anthropome-
tric, biochemical and immunological parameters includ-
ing serum albumin. For example, all five patients with
anergy in the study had a BMI < 18.5. This may suggests
that BMI could be a good tool for initial nutritional as-
sessment especially in those with low BMI as has been
observed by David E. Carney et al [18]. However, this
could be erroneous as the cut-off was not chosen based
on the function and a stunted population may still have
adequate responses. Larger studies to define malnutrition
based on cutoffs related to functional outcome rather
than arbitrary cutoffs in surgical patients are required.
Serum albumin has been used classically in popula-
tion studies as an indicator of visceral protein depletion
[22]. In present study serum albumin revealed 77.52% of
the patients to be normal although using anthropometric
data majority of them were malnourished. This does not
reflect the adequacy or deficiency of intake as many
studies and years of clinical experience have shown us
that undernourished patients do not become hypoalbu-
minemic until, and unless, they become ill. Additionally,
ill patients may become hypoalbuminemic without being
malnourished as serum albumin can be affected by acute
onset illness due to circulatory inflammatory modulators
despite normal or at least adequate nourishment.
Serum albumin has been found to be an indicator of
inflammatory activity than a nutritional marker [7,22]. In-
flammatory activity like surgery, leads to catabolism of
body cell mass. In acute disease, hypoalbuminemia can
develop quite rapidly, allowing body cell mass to be rel-
atively well preserved. If successful recovery from acute
trauma occurs without infection or residual necrotic tis-
sue etc albumin levels rise rapidly in the second half of
the first week after trauma but will be slow and will take
months to recover completely. Thus albumin levels is a
reliable sign of whether this inflammatory activity is
diminishing or increasing, in other words whether the
patient is getting better or worse [7]. This was observed
to be true in our study as we observed a difference in
outcomes based on changing albumin trends. Patients with
falling or static albumin levels (Group I) had a signifi-
cant decrease in all their nutritional parameters. Com-
pared to this, patients with increasing albumin levels
(Group II) gained significant weight and haemoglobin
with improvement in various other nutritional parameters.
This has also been observed by Visschers et al and who
have used albumin as a marker of recovery from treat-
ment, trauma or disease [23]. Haemoglobin also used as an
inflammatory activity showed a similar trend but due to
associated co-morbid conditions and failure to rule out
other causes for anemia it limited its use for this pur-
pose.
UNL, Nitrogen intake & NB calculations are widely
advocated as the best assessment tool for determining
the adequacy of nutritional support [9,10]. The methods
are simple, relatively inexpensive and can be done in any
hospital. NB has been advocated as “the standard to
which all other monitoring test should be compared”. We
found these to be useful tools for assessing the impact of
various types of surgeries on nitrogen (muscle protein)
losses in urine (UNL) and the dynamics of nutritional
support by measuring nitrogen intake (NI) in preventing
this loss.
The pattern of UNL & NB showed that the peak pro-
inflammatory activity due to surgical trauma was reached
by D6 after which the anti-inflammatory responses gradu-
ally improved the UNL & NB. Using the same method
for assessing UNL in all patients, the losses varied based
on the extent of surgery, for example it was enormously
high in patients undergoing Mc Keown esophagectomy
which involved thoracotomy and laparotomy. Assess-
ment error or small sample size could have contributed
to these high values. Despite this shortcoming, serial
measurement does give an idea about the UNL.
Adequacy of nutritional support after surgery was as-
sessed by studying the dynamics of effect of NI on UNL
on different days. Nutritional support had no impact on
these UNL till D2 after surgery as it was negatively as-
sociated. This could be due to strong pro-inflammatory
response initiated by surgical trauma causing this obli-
gate nitrogen loss. Subsequently, nutritional support helped
in reversing this trend as NI became positively asso-
ciated to UNL from D4 onwards becoming more posi-
tive till D11. This further reinforces the fact that why
nutritional support is crucial as it helps in decreasing the
UNL thereby sparing the muscle mass from breakdown.
Similar to the trend in nutritional parameters, patients
with rising albumin (Group II) showed improvement in
their NB much earlier than Group I. From being in equally
negative NB at beginning of the study, Group II became
less negative from D4 onwards coming into positive NB
by the end of the study on D11. Albumin which has tra-
ditionally been used as a marker of nutrition is a very
reliable guide for monitoring the recovery of patient
even in the first 7-10 days after surgery.
To conclude, nutritional assessment should address the
fact that malnutrition implies and suggests that some-
thing is wrong and that surgery is likely to lead to dimi-
nished healing and complications. These adverse out-
comes should dictate cut-offs rather those based on
Western populations. It is suggested to collect a larger
number of patients in future study and to correlate para-
meters of malnutrition (including functional parameters) to
postoperative infectious morbidity and mortality. This

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1388
would yield better cut-off points and more reliable as-
sessment of numbers of patients being truly malnou-
rished. Serum albumin is more reliable as an inflamma-
tory marker and a guide for knowing that patient is re-
covering from surgery than as a nutritional marker. Nu-
tritional support postoperatively helps by decreasing UNL
and NB improves better and earlier in patients with im-
proving albumin levels.
Conflict of interest statement and funding: It is ve-
rified that there was no financial conflict of interest for
all authors which includes any employment, consultancies,
stock ownership, honoraria, paid expert testimony, pa-
tent applications/registrations, and grants or other fund-
ing by any agency in the study design, in the collection,
analysis and interpretation of data; in the writing of the
manuscript; and in the decision to submit the manuscript
for publication. The following authors were part of the
study.
Ravindra Singh Mohil, Nitisha Narayan, Namrata Singh,
Asheesh Pravin Lal, Vishnubhatla Sreenivas, Dinesh
Bhatnagar
Statement of Authorship: I also verify that all the
authors have made substantial contributions to the above
study by one or more of the following:
RSM: Conception and design of the study, analysis
and interpretation of data.
NN: Acquisition of data, drafting the article
NS: Important intellectual content, statistical analysis
and interpretation of data
APL: Acquisition of data, drafting the article
VS: Statistical analysis and data interpretation.
DB: final approval of the version to be submitted
All authors have read and approved the final manu-
script and agreed to the contents.
I also verify that the manuscript, including tables has
not been previously published and that the manuscript is
not under consideration elsewhere.
REFERENCES
[1] Heymsfield, S.B., Tighe, A. and Wang, Z.-M. (1994)
Nutritional assessment by anthropometric and biochemi-
cal methods. In: Shils, M.E., Olson, J.A. and Shike, M.,
Eds., Modern Nutrition in Health and Disease, Lea and
Febiger, Malvern, 812-841.
[2] “BAPEN-Malnutrition Advisory Group: Guidelines for
detection and management of malnutrition, Essex: BAPEN,
2000.
[3] Singh, H., Watt, K., Veitch, R., Cantor, M. and Duerksen,
D. R., (2006) Malnutrition is prevalent in hospitalised
medical patients: Are house staff identifying the mal-
nourished patients?” Nutrition, 22, 352-354.
[4] Bavelaar, J.W., Otter, C.D., van Bodegraven, A.A., Thijs,
A., VanBokhorst de Vander Scueren, M.A. (2008) Di-
agnosis and treatment of a (disease-related) in hospital
malnutrition: The performance of medical and nursing
staff. Clinical Nutrition, 27, 431-438.
[5] Ben-Ishay, O., Gertsenzon, H., Mashiach, T., Kluger, Y.,
Chermesh, I. (2011) Malnutrition in Surgical Wards: A
plea for Concern. Gastroenterology Research and Pra c t i c e,
840512.
[6] Norman, K., Pichard, C., Lochs, H. and Pirlich, M. (2008)
Prognostic impact of disease-related malnutrition. Clinical
Nutrition, 27, 5-15.
[7] Soeters, P.B., Reijven, P.L., van Bokhorst-de van der
Schueren, M.A., Schols, J.M., Halfens, R.J., Meijers, J.M.
and van Gemert, W.G. (2008) A rational approach to nu-
tritional assessment. Clinical Nutrition, 27, 706-716.
[8] Michael, L.C., Karen S., Stacy, J.B. and Marhew, W.L.
(2006) Nitrogen balance, protein loss and the open ab-
domen. Critical Care Medicine, 35, 127-131.
[9] ASPEN Board of Directors and the Clinical Guidelines
Task Force (2002) Guidelines for the use of parenteral and
enteral nutrition in adult and pediatric patients. Journal of
Parenteral and Enteral Nutrition, 26, 1SA-138SA
[10] Bistrian, B.R., Blackburn, G.L., Vitale, J., Cochran, d. and
Naylor, J. (1976) Prevalence of malnutrition in general
medical patients. Journal of the American Medical Asso-
ciation, 235, 1567-1570.
[11] Gopalan, C., Rama, B.V, Sastri, S.C., Balasubramaniam,
B.S., Narasinga, R., Deosthale, Y.G. and Pant, K.C.
(2002) Nutritive Value of Indian Foods.
[12] Hawk, P.B. and Oser, B.L. (1976) Urinary Creatinine
excretion and lean body mass. The American Journal of
Clinical Nutrition, 29, 1359.
[13] Herendon, D.N. (1981) Nutritional assessment in surgical
patients. In: Yaraborough, M.F. and Curreri, P.W. Eds.,
Contemporary Issues in Clinical Nutrition, 1-11.
[14] Krishnan Das, K.V. (1980) Nutritional anemias in India.
Journal of Association of Physicians of India, 28, 521.
[15] Grant, J.P., Custer, P.B. and Thurlow, R.D. (1981) Current
techniques of nutritional assessment. Surgical Clinics of
North America, 61, 437.
[16] Palmar, D.L. and Read, W.P. (1974) Delayed hypersensi-
tivity skin testing: Clinical correlates and anergy. Journal
of Infectious Diseases, 130, 138.
[17] Leardi, S., Altilia, F., Delmonaco, S., Cianca, G., Pietro-
letti, R. and Simi, M. (2000) Blood levels of cholesterol
and postoperative septic complications. Annali Italiani
Di Chirurgia, 71, 233-237.
[18] David, E.C. and Michael, M.M. (2002) Current concepts
in nutritional assessment. Archives of Surgery, 137, 42-
45.
[19] Lochs, H., Allison, S.P., Meir, R., Pirlich, M., Kondrup,
J., Schneider, S., van den Berghe G. and Pichard, C. (2006)
Introductory to the ESPEN guidelines on enteral nutrition:
Terminology, definitions and general topics. Clinical
Nutrition, 25, 180-186.
[20] Naidu, A.N. and Rao, N.P. (1994) Body mass index: A
measure of the nutritional status in Indian populations.
European Journal of Clinical Nutrition, 48, 1994, S131-
140.
[21] Pham, N.V., Cox-Reijven, P.L., Wodzig, W.K., Greve,
J.W. and Soeters, P.B. (2007) SGA and measures for
muscle mass and strength in surgical Vietnamese patients.
Nutrition, 23, 283-291.

R. S. Mohil et al. / Health 2 (2010) 1382-1389
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1389
[22] Banh, L. (2006) Serum proteins as markers of nutrition:
What are we treating? Practice Gastroenterology, 30,
46-64.
[23] Visschers, R.G., Olde Damink, S.W., Winkens, B., Soeters,
P.B. and van Gemert, W.G. (2008) Treatment strategies in
135 consecutive patients with enterocutaneous fistulas.
World Journal of Surgery, 32, 445-453.